{"id":"W3015062804","doi":"10.1093/bioinformatics/btaa232","title":"CircMiner: accurate and rapid detection of circular RNA through splice-aware pseudo-alignment scheme","year":2020,"lang":"en","type":"article","venue":"Bioinformatics","topic":"Circular RNAs in diseases","field":"Biochemistry, Genetics and Molecular Biology","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Scheme (mathematics); splice; Circular RNA; Computer science; RNA; Computational biology; Algorithm; Mathematics; Biology; Genetics; Gene","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007903238,0.0001741024,0.0001831428,0.00002336817,0.00006025011,0.00002165207,0.0001703423,0.000128125,0.00001683292],"category_scores_gemma":[0.0001226188,0.0001735501,0.0001067398,0.0001145913,0.0000921238,0.00002008792,0.000168868,0.00006862682,0.00001046126],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001159864,"about_ca_system_score_gemma":0.00004503244,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005216257,"about_ca_topic_score_gemma":9.000998e-7,"domain_scores_codex":[0.9990187,0.00002222166,0.0003831664,0.0001850112,0.0001996761,0.000191272],"domain_scores_gemma":[0.9992493,0.000008614682,0.0002058936,0.0003299592,0.00007923973,0.0001269553],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00006805668,0.00005264257,0.0007005713,0.0006444081,0.0001851288,0.000003515069,0.0006188348,0.00008750599,0.9841869,0.00004760843,0.001105189,0.01229967],"study_design_scores_gemma":[0.001284135,0.0004186004,0.001328332,0.00004847007,0.0001014839,0.00003807835,0.00124499,0.01509074,0.9533105,0.00004844374,0.02663129,0.0004548786],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9070508,0.002439371,0.08865228,0.0002408504,0.0001405668,0.0004448211,0.0001009571,0.0000429184,0.0008874051],"genre_scores_gemma":[0.9938648,0.0009136939,0.004251125,0.0007093681,0.0001265068,0.00001303876,0.00009245519,0.00002033639,0.000008626765],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08681402,"threshold_uncertainty_score":0.7077166,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01997231376495287,"score_gpt":0.2463254117506706,"score_spread":0.2263530979857177,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}